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The central limit theorem states that the distribution of the sum of a set of random variables approaches the normal distribution as the number of variables increases, provided they are independent and some other weak conditions (such as Liapounov's conditions) are met.  These conditions will always be met if they are identically distributed and their means and standard deviations exist.

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